Modeling Link Quality for High-Speed Railway Networks Based on Hidden Markov Chain

摘要

To design efficient high-speed railway (HSR) communication systems, it is essential to characterize the wireless link quality. In this paper, we made a large amount of field investigations on link quality of HSR network, and built a practical model to reflect the changing pattern of link quality along HSR lines in terms of round trip time (RTT) and packet loss rate (PLR). After analyzing a great number of collected dataset of RTT and PLR we excitedly found that their behaviors presented an obvious two-scale time-varying phenomenon. To this end, we analyzed the potential reasons and further characterized link quality of HSR network using a generalized reference model based on hidden Markov chain. An improved forward induction algorithm was proposed to simulate the two-time-scale phenomenon of RTT and PLR. Evaluation results show that the proposed model is able to well reflect the network link quality varying along the HSR line with accuracies of 71.2% and 63.5% in terms of PLR and RTT. The proposed model can be used to guide the HSR link quality prediction and evaluation.